mirror of
https://github.com/XaverKlemenschits/jupyter-c-kernel.git
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83 lines
2.9 KiB
Markdown
83 lines
2.9 KiB
Markdown
# C kernel for Jupyter
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This project was forked from [https://github.com/brendan-rius/jupyter-c-kernel](brendan-rius/jupyter-c-kernel) as that project seems to have been abandoned. (PR is pending)
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This project includes fixes to many issues reported in [https://github.com/brendan-rius/jupyter-c-kernel](brendan-rius/jupyter-c-kernel), as well as the following additional features:
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* Option for buffered output to mimic command line behaviour (useful for teaching, default is on)
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* Command line input via `scanf` and `getchar`
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* Support for `C89`/`ANSI C` (all newer versions were already supported and still are)
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Following limitations compared to command line execution exist:
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* Input is always buffered due to limitations of the jupyter interface
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* When using `-ansi` or `-std=C89`, glibc still has to support at least `C99` for the interfacing with jupyter (this should not be an issue on an OS made after 2000)
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## Use with Docker (recommended)
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* `docker pull xaverklemenschits/jupyter-c-kernel`
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* `docker run -p 8888:8888 xaverklemenschits/jupyter-c-kernel`
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* Copy the given URL containing the token, and browse to it. For instance:
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```bash
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Copy/paste this URL into your browser when you connect for the first time,
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to login with a token:
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http://localhost:8888/?token=66750c80bd0788f6ba15760aadz53beb9a9fb4cf8ac15ce8
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```
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## Manual installation
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Works only on Linux and OS X. Windows is not supported yet. If you want to use this project on Windows, please use Docker.
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* Make sure you have the following requirements installed:
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* gcc
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* jupyter
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* python 3
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* pip
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### Step-by-step
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```bash
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git clone https://github.com/XaverKlemenschits/jupyter-c-kernel.git
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cd jupyter-c-kernel
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pip install -e . # for system install: sudo install .
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cd jupyter_c_kernel && install_c_kernel --user # for sys install: sudo install_c_kernel
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# now you can start the notebook
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jupyter notebook
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```
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## Example of notebook
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## Custom compilation flags
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You can use custom compilation flags like so:
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Here, the `-lm` flag is passed so you can use the math library.
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## Contributing
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The docker image installs the kernel in editable mode, meaning that you can
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change the code in real-time in Docker. For that, just run the docker box like
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that:
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```bash
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git clone https://github.com/XaverKlemenschits/jupyter-c-kernel.git
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cd jupyter-c-kernel
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docker build -t myName/jupyter .
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docker run -v $(pwd):/tmp/jupyter_c_kernel/ -p 8888:8888 myName/jupyter
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```
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This clones the source, run the kernel, and binds the current folder (the one
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you just cloned) to the corresponding folder in Docker.
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Now, if you change the source, it will be reflected in [http://localhost:8888](http://localhost:8888)
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instantly. Do not forget to click "restart" the kernel on the page as it does
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not auto-restart.
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## License
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[MIT](LICENSE.txt)
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